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An algorithm for learning rule sets from survival data
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README.md

README.md

LR-Rules

An algorithm for learning rule sets from survival data

Installation and usage

Please see the Release tab to download software and user's manual.

Citing

Wrobel, L, Gudys, A, Sikora, M (2017) Learning rule sets from survival data, BMC Bioinformatics, 2017 May 30;18(1):285. DOI: 10.1186/s12859-017-1693-x.

Data availability

  • actg320 (HIV-infected patients): ftp://ftp.wiley.com/public/sci_tech_med/survival
  • BMT-Ch (bone marrow transplant): available on request (lukasz.wrobel@polsl.pl)
  • cancer (advanced lung cancer patients): survival R package
  • follic (follicular cell lymphoma patients): randomForestSRC R package
  • GBSG2 (node-positive breast cancer patients): TH.data R package
  • hd (Hodgkin's disease patients): randomForestSRC R package
  • LAC (lung adenocarcinoma): pensim R package
  • lung (early detection of lung cancer): ​https://www.stats.ox.ac.uk/pub/datasets/csb
  • Melanoma (malignant melanoma patients after radical operation): riskRegression R package
  • mgus (patients with monoclonal gammopathy of undetermined significance): survival R package
  • pbc (primary biliary cirrhosis of the liver): survival R package
  • PTC (papillary thyroid carcinoma): https://github.com/adaa-polsl/LR-Rules/blob/master/data/thyroid.arff
  • std (occurrence of sexually transmitted diseases): KMsurv R package
  • uis (drug abuse reduction): quantreg R package
  • wcgs (occurrence of coronary heart disease): epitools R package
  • whas1 (myocardial infarction patients, 1st book edition): ​ftp://ftp.wiley.com/public/sci_tech_med/survival
  • whas500 (myocardial infarction patients, 2nd book edition): ​ftp://ftp.wiley.com/public/sci_tech_med/survival
  • zinc (esophageal cancer): NestedCohort R package
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